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Large Language Models (LLMs), like ChatGPT, have demonstrated vast potential but also introduce challenges related to content constraints and potential misuse. Our study investigates three key research questions: (1) the number of different…

软件工程 · 计算机科学 2024-03-12 Yi Liu , Gelei Deng , Zhengzi Xu , Yuekang Li , Yaowen Zheng , Ying Zhang , Lida Zhao , Tianwei Zhang , Kailong Wang , Yang Liu

Recent explorations with commercial Large Language Models (LLMs) have shown that non-expert users can jailbreak LLMs by simply manipulating their prompts; resulting in degenerate output behavior, privacy and security breaches, offensive…

计算与语言 · 计算机科学 2024-03-28 Abhinav Rao , Sachin Vashistha , Atharva Naik , Somak Aditya , Monojit Choudhury

Large Language Models (LLMs) are increasingly vulnerable to a sophisticated form of adversarial prompting known as camouflaged jailbreaking. This method embeds malicious intent within seemingly benign language to evade existing safety…

密码学与安全 · 计算机科学 2025-09-09 Youjia Zheng , Mohammad Zandsalimy , Shanu Sushmita

Large Language Models (LLMs) have increasingly become pivotal in content generation with notable societal impact. These models hold the potential to generate content that could be deemed harmful.Efforts to mitigate this risk include…

计算与语言 · 计算机科学 2024-08-20 Kexin Chen , Yi Liu , Dongxia Wang , Jiaying Chen , Wenhai Wang

Large Language Models (LLMs), such as ChatGPT, encounter `jailbreak' challenges, wherein safeguards are circumvented to generate ethically harmful prompts. This study introduces a straightforward black-box method for efficiently crafting…

计算与语言 · 计算机科学 2024-04-25 Kazuhiro Takemoto

The adoption of large language models (LLMs) in many applications, from customer service chat bots and software development assistants to more capable agentic systems necessitates research into how to secure these systems. Attacks like…

密码学与安全 · 计算机科学 2024-12-03 Erick Galinkin , Martin Sablotny

Large Language Models (LLMs) suffer from a range of vulnerabilities that allow malicious users to solicit undesirable responses through manipulation of the input text. These so-called jailbreak prompts are designed to trick the LLM into…

计算与语言 · 计算机科学 2025-10-13 John Hawkins , Aditya Pramar , Rodney Beard , Rohitash Chandra

Jailbreaking large language models (LLMs) has emerged as a critical security challenge with the widespread deployment of conversational AI systems. Adversarial users exploit these models through carefully crafted prompts to elicit…

密码学与安全 · 计算机科学 2026-02-23 Sri Durga Sai Sowmya Kadali , Evangelos E. Papalexakis

Recent advancements in generative AI have enabled ubiquitous access to large language models (LLMs). Empowered by their exceptional capabilities to understand and generate human-like text, these models are being increasingly integrated into…

密码学与安全 · 计算机科学 2024-10-02 Zhiyuan Yu , Xiaogeng Liu , Shunning Liang , Zach Cameron , Chaowei Xiao , Ning Zhang

Jailbreak attacks cause large language models (LLMs) to generate harmful, unethical, or otherwise objectionable content. Evaluating these attacks presents a number of challenges, which the current collection of benchmarks and evaluation…

As the integration of the Large Language Models (LLMs) into various applications increases, so does their susceptibility to misuse, raising significant security concerns. Numerous jailbreak attacks have been proposed to assess the security…

密码学与安全 · 计算机科学 2025-05-30 Bijoy Ahmed Saiem , MD Sadik Hossain Shanto , Rakib Ahsan , Md Rafi ur Rashid

While large language models (LLMs) exhibit remarkable capabilities across a wide range of tasks, they pose potential safety concerns, such as the ``jailbreak'' problem, wherein malicious instructions can manipulate LLMs to exhibit…

计算与语言 · 计算机科学 2024-03-05 Yue Deng , Wenxuan Zhang , Sinno Jialin Pan , Lidong Bing

Large Language Models (LLMs), such as ChatGPT and GPT-4, are designed to provide useful and safe responses. However, adversarial prompts known as 'jailbreaks' can circumvent safeguards, leading LLMs to generate potentially harmful content.…

计算与语言 · 计算机科学 2024-04-09 Peng Ding , Jun Kuang , Dan Ma , Xuezhi Cao , Yunsen Xian , Jiajun Chen , Shujian Huang

Jailbreaking is an emerging adversarial attack that bypasses the safety alignment deployed in off-the-shelf large language models (LLMs). A considerable amount of research exists proposing more effective jailbreak attacks, including the…

密码学与安全 · 计算机科学 2024-03-05 Daoyuan Wu , Shuai Wang , Yang Liu , Ning Liu

Jailbreaks have been a central focus of research regarding the safety and reliability of large language models (LLMs), yet the mechanisms underlying these attacks remain poorly understood. While previous studies have predominantly relied on…

密码学与安全 · 计算机科学 2025-11-04 Nathalie Kirch , Constantin Weisser , Severin Field , Helen Yannakoudakis , Stephen Casper

Large language models (LLMs) are susceptible to a type of attack known as jailbreaking, which misleads LLMs to output harmful contents. Although there are diverse jailbreak attack strategies, there is no unified understanding on why some…

计算与语言 · 计算机科学 2024-12-04 Yuping Lin , Pengfei He , Han Xu , Yue Xing , Makoto Yamada , Hui Liu , Jiliang Tang

Large Language Models (LLMs) are widely deployed in real-world systems. Given their broader applicability, prompt engineering has become an efficient tool for resource-scarce organizations to adopt LLMs for their own purposes. At the same…

密码学与安全 · 计算机科学 2026-02-27 Piyush Jaiswal , Aaditya Pratap , Shreyansh Saraswati , Harsh Kasyap , Somanath Tripathy

Large Language Models (LLMs) are deployed in interactive contexts with direct user engagement, such as chatbots and writing assistants. These deployments are vulnerable to prompt injection and jailbreaking (collectively, prompt hacking), in…

Jailbreak attacks induce Large Language Models (LLMs) to generate harmful responses, posing severe misuse threats. Though research on jailbreak attacks and defenses is emerging, there is no consensus on evaluating jailbreaks, i.e., the…

密码学与安全 · 计算机科学 2025-02-05 Delong Ran , Jinyuan Liu , Yichen Gong , Jingyi Zheng , Xinlei He , Tianshuo Cong , Anyu Wang

Jailbreak attacks represent one of the most sophisticated threats to the security of large language models (LLMs). To deal with such risks, we introduce an innovative framework that can help evaluate the effectiveness of jailbreak attacks…

计算与语言 · 计算机科学 2025-03-19 Dong Shu , Chong Zhang , Mingyu Jin , Zihao Zhou , Lingyao Li , Yongfeng Zhang
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